Medication administration errors are among the most prevalent and costly challenges to patient safety. Administration of drugs by intravenous (IV) injection is one of the most common medical procedures. Simulation-based healthcare training offers the ability for trainees to practice drug injection safely and with quantitative feedback on their performance. Because of the importance of training correct administration of drugs by intravenous (IV) injection, some commercial medical simulators include the ability for a trainee to inject fluid into an IV port, with concomitant sensing of the volume and identity of the drug being injected. The actual fluid injected is not a real drug, but instead a drug simulant, which is typically water or saline. Such simulants are both far less expensive and far safer to employ in a training environment compared to real medications. Current medical simulator injection sensing systems are typically built into higher-cost patient simulators. These simulators consist of physical models of a human body (mannequins) that contain a variety of mechatronic components such as sensors and actuators, and a computer control system.
Many commercial simulators, particularly lower-cost simulators, lack the ability to sense injection parameters such as volume, injection rate, and identity of simulated drug, and there is typically no way to add this functionality to existing simulators: they are closed, non-upgradable systems, and the only way for end-users to add this functionality is via a high cost purchase of a new simulator.
Current medical simulators use flow meters to measure the volume of drug simulant injected into the system. Such volume measurements may then feed into physiological models which the simulator utilizes to produce a realistic response. Presently, components of simulators that measure the volume and detect the identity of injected drug simulants are typically located inside the simulators, thus making it difficult for simulation training centers to add such components to existing medical simulators or modify them in any way. If such modifications are attempted, they may void the warranty of the existing simulator. Because simulators can cost upwards of $100,000, it can be cost-prohibitive for medical simulation facilities to purchase new or upgraded simulators as new drug injection training technology becomes available.
In addition, there are significant limitations in the capabilities of existing drug simulant recognition systems. For example, radio-frequency identification (RFID) tags may be attached to a syringe and encoded with a number that associates the syringe with a particular medication. An RFID receiver may then be built into the arm of the medical simulator. But this system fails when more than one syringe is placed near the simulator: the system detects multiple RFID tags, and cannot disambiguate between them. Human operator intervention is then required to observe which of the several syringes is being used by a trainee, and the human operator manually enters the information into the control software for the simulator. This, of course, defeats the purpose of having an automatic drug injection recognition system.
In addition, it would be useful to offer drug injection sensing and measurement capabilities in other simulation-based training contexts and application areas in addition to mannequin-based simulators. These include standardized patients (actors who play the role of a patient for training purposes) and field exercises involving persons playing the role of victims of a mass-casualty event. In both settings, training in the selection and administration of injectable drugs is a critical learning point, but obviously injecting into a real person is not possible. A system that offered the ability to simulate injection into human actors and measure and transmit data on injection parameters would provide important feedback to both trainees and instructors regarding correct diagnosis, drug selection and administration technique.
Accordingly, a need exists for solutions for training drug injection which may be readily incorporated with other existing training solutions or human actors, which provides quantitative feedback, which may be provided at a cost effective manner, and which offers performance improvements compared to current systems.